A robust data-driven version of the Berlin Method

dc.contributor.authorFeng, Yuanhua
dc.contributor.authorHeiler, Siegfried
dc.date.accessioned2011-03-25T09:40:27Zdeu
dc.date.available2011-03-25T09:40:27Zdeu
dc.date.issued2000deu
dc.description.abstractIn this paper a robust data-driven procedure for decomposing seasonal time series based on a generalized Berlin Method (BV, Berliner Verfahren) as proposed by Heiler and Michels (1994) is discussed. The basic robust algorithm used here is an adaptation of the LOWESS (LOcally Weighted Scatterplot Smoothing) procedure (Cleveland, 1979). For selecting the optimal bandwidth the simple double smoothing rule (Heiler and Feng, 1999) is used. The optimal order of the local polynomial is selected with a BIC criterion. The proposed procedure is applied to the macroeconomic time series used in the recent empirical studies carried out by the German Federal Statistical Office (Speth, 1994 and Höpfner, 1998).eng
dc.description.versionpublished
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dc.identifier.ppn08885082Xdeu
dc.identifier.urihttp://kops.uni-konstanz.de/handle/123456789/11817
dc.language.isoengdeu
dc.legacy.dateIssued2000deu
dc.relation.ispartofseriesCoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie
dc.rightsterms-of-usedeu
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/deu
dc.subjecttime series decompositiondeu
dc.subjectrobust estimationdeu
dc.subjectbandwidth selectiondeu
dc.subject.ddc330deu
dc.titleA robust data-driven version of the Berlin Methodeng
dc.typeWORKINGPAPERdeu
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kops.bibliographicInfo.seriesNumber2000/15deu
kops.citation.bibtex
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  year={2000},
  series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
  title={A robust data-driven version of the Berlin Method},
  number={2000/15},
  author={Feng, Yuanhua and Heiler, Siegfried}
}
kops.citation.iso690FENG, Yuanhua, Siegfried HEILER, 2000. A robust data-driven version of the Berlin Methoddeu
kops.citation.iso690FENG, Yuanhua, Siegfried HEILER, 2000. A robust data-driven version of the Berlin Methodeng
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